HBS Digital Initiative builds community and expertise around digital transformation and tech at Harvard Business School and beyond. We manage this forum to gather and share perspectives from the HBS student community.

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Jaclyn – great work here. Though the product outsourcing seems like a great idea and it has worked well, I’m reminded of something we talked about during our Gap case in Marketing – consumers are very bad at predicting their own future preferences. The issue may be less prevalent here given tastes in toys may be less fickle than tastes in clothes. However, there will be a delay from the time LEGO sources ideas from customers to the time the products appear on store shelves. I wonder if they have much exposure to consumer preferences changing during the “throughput time” of the product. All in, though, it may still yield better results than creating products without consumer input.

Matt – very interesting topic. As others have mentioned, I have concerns around (i) how to incentivize people and (ii) how to protect against potential cultural biases. On the one hand, incentivizing people to submit as much data as possible will likely provide useful information that may prevent an attack. On the flip side, we need to weigh that against all of the “false positives” that this system will cause, especially if people are rewarded for providing information. Furthermore, this may lead to security concerns among ordinary citizens who are looking to report information on others for their own financial gain.

Anything we can do to prevent future attacks is immensely valuable. That said, we will need to decide as a society whether the trade-offs to our personal security are worth it.

Elizabeth – terrific article. One point that stood out to me was around the potential for 3D printing not only to help customize shoes and lower manufacturing costs, but also for it to aid with Nike’s goal of reducing environmental impact. Once additive manufacturing is better proven and cheaper, I agree with your recommendation that Nike should invest heavily in the space. Increasing customization, reducing costs, and lowering carbon footprint are all high priorities for the company that can be elegantly solved through this technology.

TomTom – nice work here. From a TOM perspective, it seems that 3D printing is great for the innovation process as it greatly reduces the “throughput time” of producing a prototype. However, I worry that the mass produced 3D shoes may introduce quite a few operations issues. Given one of the strengths of 3D printing is that it allows customization, I think it would be wise to offer that to customers (especially as the assembly line is currently cheaper for a mass produced model). That said, allowing everyone to customize his or her shoes could prove to be a logistics nightmare as the number of Adidas SKUs effectively becomes infinity. For that reason, this may remain a niche product until the 3D printing cost structure changes materially and replaces the mass production assembly line.

M – Very nice article. I wonder whether there is a ceiling to how much machine learning can control decision making in financial markets independent of human judgement. It reminds me of a recent talk I attended at HBS in which Jamie Dimon and Seth Klarman were asked about the rise of passive investing. Both acknowledged that the asset class has grown tremendously and has its advantages, but each stated that there is a limit to how large this passive segment can be. The reason is that if no humans are monitoring the market and everything is passive or machine based, eventually alpha-generating opportunities will arise, in which case it is worthwhile for a human to actively do his / her homework analyzing securities. I believe this same idea will hold with machine learning in which there is ultimately a limit to how many funds can run algorithms that trade independent of human judgement (outside of writing the algorithm). It will be interesting to see how this trend unfolds.

Bo G – very nice article. The Toronto Raptors are a very interesting test case in my mind given their recent trade for Kawhi Leonard, an all-NBA player who has lingering questions about his health and attitude. The article mentions that Watson is able to screen interviews and social media to get a read on a player’s cultural fit, but I wonder (i) how well it can actually do this and (ii) how it could account for Kawhi’s questionable health. Separately, I wonder how well Watson works in the context of the NBA in which adding a player like Kawhi materially affects the rest of the team (in contrast to baseball where each player operates in a mostly independent manner). If anything, these questions point to why there is a continued need for human oversight – Watson can be seen as more of an unbiased viewpoint rather than the source of truth for NBA GMs.